Integrated Framework for Software Cost Estimation Models - Arshad, Ali
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Cost Estimation has always remained a focus area for researchers of different fields Software cost estimation is a complex activity that requires knowledge of a number of key attributes about the project. On the other hand there are diverse kinds of techniques available to predict cost estimation, each of which is having certain pros and cons. Line of code (LOC) can be considered as one of the earliest methods used for estimation purpose, i.e. how much a lines of code a programmer/developer has written on a punch card. With the emergence of high level languages and then advancement in coding…mehr

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Produktbeschreibung
Cost Estimation has always remained a focus area for researchers of different fields Software cost estimation is a complex activity that requires knowledge of a number of key attributes about the project. On the other hand there are diverse kinds of techniques available to predict cost estimation, each of which is having certain pros and cons. Line of code (LOC) can be considered as one of the earliest methods used for estimation purpose, i.e. how much a lines of code a programmer/developer has written on a punch card. With the emergence of high level languages and then advancement in coding environment, the LOC became insufficient. Therefore researchers were forced to come up with new and innovative ideas in this domain. All around the world, currently many tools, techniques and strategies are being practiced. Pakistan, being one of the heavily outsourced countries, thanking to its cheap labor, has also employed some techniques for cost estimation. This study is focused on Pakistani software houses with intention of exploring the software cost estimation methods, models and techniques along with current state of practice.
Autorenporträt
Ali Arshad is a PhD Scholar in Xidian University, Xian,china currently and research intrests are software cost estimation, software architecture and Machine learning areas. Currently working on Semi Supervised Deep Fuzzy C- Mean Clustering Project. He has vast experience in Education sector and field experience.